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  Modelling the effects of formal literacy training on language mediated visual attention

Smith, A. C., Monaghan, P., & Huettig, F. (2013). Modelling the effects of formal literacy training on language mediated visual attention. In M. Knauff, M. Pauen, N. Sebanz, & I. Wachsmuth (Eds.), Proceedings of the 35th Annual Meeting of the Cognitive Science Society (CogSci 2013) (pp. 3420-3425). Austin, TX: Cognitive Science Society.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-000E-EDC6-C Version Permalink: https://hdl.handle.net/11858/00-001M-0000-0029-0900-6
Genre: Conference Paper

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Smith_2013_Cogsci.pdf (Publisher version), 416KB
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 Creators:
Smith, Alastair Charles1, 2, Author           
Monaghan, Padraic3, Author
Huettig, Falk1, 4, Author           
Affiliations:
1Psychology of Language Department, MPI for Psycholinguistics, Max Planck Society, ou_792545              
2International Max Planck Research School for Language Sciences, MPI for Psycholinguistics, Max Planck Society, Nijmegen, NL, ou_1119545              
3Department of Psychology, Lancaster University, Lancaster, LA1 4YF, UK, ou_persistent22              
4Donders Institute for Brain, Cognition and Behaviour, External Organizations, ou_55236              

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 Abstract: Recent empirical evidence suggests that language-mediated eye gaze is partly determined by level of formal literacy training. Huettig, Singh and Mishra (2011) showed that high-literate individuals' eye gaze was closely time locked to phonological overlap between a spoken target word and items presented in a visual display. In contrast, low-literate individuals' eye gaze was not related to phonological overlap, but was instead strongly influenced by semantic relationships between items. Our present study tests the hypothesis that this behavior is an emergent property of an increased ability to extract phonological structure from the speech signal, as in the case of high-literates, with low-literates more reliant on more coarse grained structure. This hypothesis was tested using a neural network model, that integrates linguistic information extracted from the speech signal with visual and semantic information within a central resource. We demonstrate that contrasts in fixation behavior similar to those observed between high and low literates emerge when models are trained on speech signals of contrasting granularity.

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Language(s): eng - English
 Dates: 2013-02-012013-04-022013-07-24
 Publication Status: Published online
 Pages: 6
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
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Title: the 35th Annual Meeting of the Cognitive Science Society (CogSci 2013)
Place of Event: Berlin
Start-/End Date: 2013-07-31 - 2013-08-03

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Title: Proceedings of the 35th Annual Meeting of the Cognitive Science Society (CogSci 2013)
Source Genre: Proceedings
 Creator(s):
Knauff, M., Editor
Pauen, M., Editor
Sebanz, N., Editor
Wachsmuth, I., Editor
Affiliations:
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Publ. Info: Austin, TX : Cognitive Science Society
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 3420 - 3425 Identifier: -